An Application of DSSAT for Productivity Assessment of Sugarcane Growing Soils in Sa Kaeo Province
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Abstract
The DSSAT cropping model can determine the relationship between the environment and crop yield and can also effectively predict crop yields based on local environmental differences in different regions. This research aimed to evaluate the accuracy of the DSSAT cropping model for assessing the productivity of sugarcane growing soils in Sa Kaeo province. Data collection were soil information and plant management data in the experimental plots of the representative sugarcane growing soils in Sa Kaeo province, i.e., Thap Prik and Munchakiri soil series. The data from the experimental plots were added to the DSSAT cropping model together with the climate data and plant genetic coefficient data from reference sources. The model performance was evaluated by comparing the simulated sugarcane yields with the actual yields obtained from the experimental plot. Then, simulating mapping units were generated to evaluate sugarcane growing soil productivity in Sa Kaeo province. The results found that the sugarcane yields simulated from the DSSAT cropping model were lower than the actual yields obtained from the experimental plot, excepted stalk fresh mass. The DSSAT cropping model most precisely estimated the stalk height with a root mean square error of 0.142–0.588 and the agreement index between 0.884–0.989. The sugarcane planting simulation results using the DSSAT cropping model for estimation of the soil productivity of sugarcane growing soils in Sa Kaeo province found that the soil series with the highest sugarcane productivity potential was Thap Prik soil series, followed by Bang Khla, Wang Hai, Wang Saphung, Chiang Khan and Munchakiri soil series.
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References
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